NEXTCAR projects, short for “NEXT-Generation Energy Technologies for Connected and Automated On-Road Vehicles,” are enabling technologies that use connectivity and automation to co-optimize vehicle dynamic controls and powertrain operation, thereby reducing energy consumption of the vehicle. Vehicle dynamic and powertrain control technologies, implemented on a single vehicle basis, across a cohort of cooperating vehicles, or across the entire vehicle fleet, could significantly improve individual vehicle and, ultimately, fleet energy efficiency.
Main role: developing & implementing ECO-driving algorithms.
BEAM is a modeling Framework for Behavior, Energy, Autonomy, and Mobility. BEAM extends the Multi-Agent Transportation Simulation Framework (MATSim) to enable powerful and scalable analysis of urban transportation systems.
Main role: developing & implementing parameter estimation algorithms for a behavior model of Plug-in Electric Vehicles.
MyGreenCar is a mobile application that tracks your personal driving style (hard braker or fast accelerator), the terrain you frequent (hills or flatlands), and driving circumstances (stuck in traffic on the freeway or just putt-putting around town). It then tells you how the vehicles stack up in terms of fuel efficiency, range, and cost savings seeks to increase the adoption of clean vehicles by enabling drivers and fleet managers to understand whether clean vehicles meet their personal needs, and quantify the magnitude of fuel and cost savings from choosing a clean vehicle. MyGreenCar was a finalist of a 2017 R&D 100 Awards.
Main role: developing Android application.
V2G-Sim is a simulation platform that couples vehicle powertrain, charging, and driver usage pattern sub-modules to address vehicle-grid integration concerns in a systematic way. V2G-Sim is being developed using Laboratory Directed Research and Development (LDRD) funding at Lawrence Berkeley National Laboratory. V2G-Sim was a recipient of a 2015 R&D 100 Award. See here for more info about all of Berkeley Lab’s 2015 R&D 100 awards.
Main role: developing & implementing drive cycle generation algorithms.